使用时序出租车轨迹识别多层次城市功能结构

地理时空大数据被广泛用于城市功能结构识别，其中功能层次性的研究对于系统理解城市功能的结构特征和分布形态具有重大意义，但相关研究仍处于空缺状态。基于时序出租车出行数据和感兴趣点数据描述居民出行模式，结合动态时间规整和K-MEDOIDS聚类算法识别城市的功能属性和空间结构。研究结果表明，广州市中心城区的城市功能具有明显的层次性。随着层次细致程度的提升，其功能属性由"职-住"二元结构向"职-住-休"三元结构发展；其空间结构符合环状圈层构造，功能由外围的居住游憩向中心的商业休闲过渡，并在不同的圈层上呈现出各自的功能倾向。这为城市规划人员系统理解城市功能的属性变化和结构特征提供了有效的参考价值。

Sensing Multi-level Urban Functional Structures by Using Time Series Taxi Trajectory Data

Geospatial big data has been widely applied to distinguish urban functions. Especially, the research of functional hierarchy is of profound significance in understanding the structural characteristics and distributional forms of urban functions thoroughly, but related studies are still vacant. Therefore, this study depicts human mobility patterns based on time-series taxi trajectory data and point of interests (POIs) data, and identifies urban functional properties and spatial structures through combining dynamic time warping and K-MEDOIDS clustering algorithm. The results show that the urban functions in the central area of Guangzhou possess obvious hierarchical characteristics. With the refinement of hierarchies, the functional properties are developed from the dual-structure of working-living into the triple-structure of working-living-entertainment gradually. Moreover, the spatial structure is consistent with the ring-shaped structure, and its urban functions are gradually transformed from the living-entertainment function at outer rings into the commercial-entertainment function at central rings, and present different tendencies at different rings. This study provides efficient references for urban planners to understand the property changes and structural characteristics of urban functions.